Speaker
Description
As part of the Nuclear Physics AI-Ready Accelerator Data (NARAD) project, Brookhaven National Laboratory is developing a demonstration use case based on the Booster-to-AGS (BtA) transfer line. We establish an AI-ready representation of the BtA lattice using the Particle Accelerator Language Standard (PALS), extended with semantic metadata linking lattice elements to control system signals and device capabilities. This NARAD-PALS model enables direct mapping between simulation, operational devices, and machine data. We implement this framework for the BtA line and demonstrate semantic device queries and control-channel resolution within the BNL Accelerator Device Objects (ADO) system. This unified representation supports integration of streaming and archived data and provides a foundation for ML-based optimization of AGS injection and cross-facility interoperability.
Funding Agency
Work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, Award No. DE-SCL0000127, and under Contract Nos. DE-SC0012704, DE-AC05-06OR23177, and DE-AC05-76RL01830.
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